Collaborative Research: Advanced Coding Techniques for Next-Generation Optical Communications

近年来，互联网上的数据流量呈爆炸式增长。随着视频流媒体、云计算的普及，以及用户生成内容通过社交网络的快速传播，毫无疑问，这一趋势将持续下去。为了支持这些服务，构成互联网骨干的光传输网络上承载的数据速率一直在不断增加，预计这一趋势将继续下去。虽然正在部署每秒100千兆比特的光传输网络，但即使保守的估计也预测下一代光传输网络的数据速率将在2016年增加到每秒400千兆比特，在2019年增加到每秒1 Tera比特，在2025年增加到每秒10 Tera比特。随着数据速率的增加，光纤信道的光信噪比显著降低，误码率增加。该项目考虑设计和分析先进的纠错码，以减轻传输错误，并为互联网流量提供可靠的通信。由于硬件的限制，在极高的数据速率下设计和实现先进的信道编码技术是非常具有挑战性的。这由于期望的码率高（例如，大于0.8）并且目标误码率极低（例如，大约1 e-15或10^{-15}）。这些限制要求先进的信道编码技术的设计和跨学科的研究人员谁专注于算法设计和研究人员谁专门从事硬件实现之间的互动创新的想法。这项研究工作的目标是设计实用的代码和解码器，提供大的编码增益，并可以实现的速度扩展到10兆兆比特每秒的未来。该项目的变革性质在于，将设计和分析几种新型的代码和计算效率高的解码器。具体来说，我们将考虑以下三个主题-（i）设计和分析具有提供大编码增益潜力的新型空间耦合代数码，对称乘积码和空间耦合卷积码，（ii）设计和分析这些码的消息传递解码算法，这些算法可以在适度的硬件资源下实现极高的吞吐量，以及（iii）利用来自信道的软信息的可用性的代码和计算有效的软判决解码算法的设计。该项目的另一个重要方面是设计方法，它利用算法设计和硬件实现之间的密切互动，这将导致现场可编程门阵列上的代码和解码器的实施。该项目的更广泛的影响将通过计划的举措来最大化，这些举措旨在扩大德克萨斯A M大学和杜克大学的电信和信号处理以及超大规模集成课程的范围。它还将促进德克萨斯A M大学和杜克大学之间在教育活动的设计、开发和实施方面的合作。

In recent years, there has been an explosion of data traffic over the internet. With the popularity of video streaming, cloud computing, and the rapid dissemination of user-generated content through social networks, there is no doubt that this trend will continue. In order to support these services, the data rates carried over optical transport networks which constitute the internet backbone has been constantly increasing and this trend is expected to continue. While 100 Giga bits per second optical transport networks are being deployed, even conservative estimates predict that data rates in next generation optical transport networks will increase to 400 Giga bits per second in 2016, 1 Tera bits per second in 2019 and 10 Tera bits per second in 2025. As the data rate increases, optical signal-to-noise ratio of the fiber-optic channel decreases substantially and the bit error-rate increases. This project considers the design and analysis of advanced error-correcting codes that mitigate transmission errors and provide reliable communication for internet traffic. The design and implementation of advanced channel coding techniques at extremely high data rates is very challenging due to hardware constraints. This is exacerbated by the fact that the desired code rates are high (e.g., greater than 0.8) and the target bit error rates are extremely low (e.g., on the order of 1e-15 or 10^{-15}). These constraints call for innovative ideas for the design of advanced channel coding techniques and cross-disciplinary interaction between researchers who focus on algorithm design and researchers who specialize in hardware implementation. The goal of this research effort is to design practical codes and decoders that provide large coding gains and can be implemented at speeds scaling to 10 Tera bits per second in the future. The transformative nature of the project lies in the fact that several novel classes of codes and computationally-efficient decoders will be designed and analyzed. Specifically, we will consider the following three topics - (i) the design and analysis of novel classes of spatially-coupled algebraic codes, symmetric product codes and spatially-coupled convolutional codes that have the potential to deliver large coding gains, (ii) the design and analysis of message-passing decoding algorithms for these codes that can achieve extremely high throughput with moderate hardware resources, and (iii) the design of codes and computationally-efficient soft-decision decoding algorithms that exploit the availability of soft information from the channel. Another important aspect of this project is the design methodology which leverages the close interaction between algorithm design and hardware implementation which will result in the implementation of codes and decoders on field programmable gate arrays. The broader impacts of this project will be maximized by the planned initiatives that aim to expand the scope of the telecommunications and signal processing and very large scale integration curricula at Texas A&M University and Duke University. It will also promote collaboration in the design, development and implementation of educational activities between Texas A&M University and Duke University.